Robust navigation techniques for the GVG-based slam in unstructured environment

Sunghwan Ahn; Nakju Lett Doh; Wan Kyun Chung

doi:10.3182/20050703-6-cz-1902.01347

Robust navigation techniques for the GVG-based slam in unstructured environment

Sunghwan Ahn, Nakju Lett Doh, Wan Kyun Chung

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

The Generalized Voronoi Graph (GVG) has been effectively used for the SLAM and navigation of mobile robots. Since the mobile robot should perform the GVG-based SLAM and navigation in unstructured environments using inaccurate noisy sensors, it requires accurate data association and robust navigation techniques. in this paper, we suggest three techniques for a robust construction of the GVG. The first one is a robust node matching technique and the second one is an adaptable sensor area matching method for the robust exploration. Finally we propose a technique which is capable of distinguishing between closely located nodes. The simulation results show that the proposed algorithm can work successfully under 20% errors of odometry and range sensor in unstructured environment.

Original language	English
Title of host publication	Proceedings of the 16th IFAC World Congress, IFAC 2005
Publisher	IFAC Secretariat
Pages	463-468
Number of pages	6
ISBN (Print)	008045108X, 9780080451084
DOIs	https://doi.org/10.3182/20050703-6-cz-1902.01347
Publication status	Published - 2005
Externally published	Yes

Publication series

Name	IFAC Proceedings Volumes (IFAC-PapersOnline)
Volume	16
ISSN (Print)	1474-6670

Keywords

Generalized Voronoi Graph (GVG)
Mobile robots
Node matching
Topological localization

ASJC Scopus subject areas

Control and Systems Engineering

Access to Document

10.3182/20050703-6-cz-1902.01347

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title = "Robust navigation techniques for the GVG-based slam in unstructured environment",

abstract = "The Generalized Voronoi Graph (GVG) has been effectively used for the SLAM and navigation of mobile robots. Since the mobile robot should perform the GVG-based SLAM and navigation in unstructured environments using inaccurate noisy sensors, it requires accurate data association and robust navigation techniques. in this paper, we suggest three techniques for a robust construction of the GVG. The first one is a robust node matching technique and the second one is an adaptable sensor area matching method for the robust exploration. Finally we propose a technique which is capable of distinguishing between closely located nodes. The simulation results show that the proposed algorithm can work successfully under 20% errors of odometry and range sensor in unstructured environment.",

keywords = "Generalized Voronoi Graph (GVG), Mobile robots, Node matching, Topological localization",

author = "Sunghwan Ahn and Doh, {Nakju Lett} and Chung, {Wan Kyun}",

year = "2005",

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AU - Doh, Nakju Lett

AU - Chung, Wan Kyun

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N2 - The Generalized Voronoi Graph (GVG) has been effectively used for the SLAM and navigation of mobile robots. Since the mobile robot should perform the GVG-based SLAM and navigation in unstructured environments using inaccurate noisy sensors, it requires accurate data association and robust navigation techniques. in this paper, we suggest three techniques for a robust construction of the GVG. The first one is a robust node matching technique and the second one is an adaptable sensor area matching method for the robust exploration. Finally we propose a technique which is capable of distinguishing between closely located nodes. The simulation results show that the proposed algorithm can work successfully under 20% errors of odometry and range sensor in unstructured environment.

AB - The Generalized Voronoi Graph (GVG) has been effectively used for the SLAM and navigation of mobile robots. Since the mobile robot should perform the GVG-based SLAM and navigation in unstructured environments using inaccurate noisy sensors, it requires accurate data association and robust navigation techniques. in this paper, we suggest three techniques for a robust construction of the GVG. The first one is a robust node matching technique and the second one is an adaptable sensor area matching method for the robust exploration. Finally we propose a technique which is capable of distinguishing between closely located nodes. The simulation results show that the proposed algorithm can work successfully under 20% errors of odometry and range sensor in unstructured environment.

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